TY - GEN
T1 - Industrial polymerization process quality prediction based on CPSO-LSTM-RNN
AU - Wang, Xuesong
AU - Bo, Cuimei
AU - Li, Jun
N1 - Publisher Copyright:
© VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.
PY - 2022
Y1 - 2022
N2 - Due to the industrial polymer process is a complex and nonlinear process with the characteristic of multi-variables, hysteresis, large inertia and strong coupling, the main production targets are difficult to measure accurately, and there are fluctuations in data information during the production, so many production data need to be analyzed and processed. Therefore, this paper proposes the CPSO-LSTM-RNN algorithm to predict the yield of industrial polymer process. Firstly, the LSTM-RNN model is established and the model is trained with the data of the production process. Then, the CPSO algorithm is used to obtain the optimal hyperparameters of the model. Finally, the validity of the model is verified by a set of industrial data of the polymerization process.
AB - Due to the industrial polymer process is a complex and nonlinear process with the characteristic of multi-variables, hysteresis, large inertia and strong coupling, the main production targets are difficult to measure accurately, and there are fluctuations in data information during the production, so many production data need to be analyzed and processed. Therefore, this paper proposes the CPSO-LSTM-RNN algorithm to predict the yield of industrial polymer process. Firstly, the LSTM-RNN model is established and the model is trained with the data of the production process. Then, the CPSO algorithm is used to obtain the optimal hyperparameters of the model. Finally, the validity of the model is verified by a set of industrial data of the polymerization process.
UR - http://www.scopus.com/inward/record.url?scp=85165959320&partnerID=8YFLogxK
M3 - 会议稿件
AN - SCOPUS:85165959320
T3 - ECITech 2022 - 2022 International Conference on Electrical, Control and Information Technology
SP - 808
EP - 811
BT - ECITech 2022 - 2022 International Conference on Electrical, Control and Information Technology
A2 - Campi, Marco C.
A2 - Wang, Ning
PB - VDE VERLAG GMBH
T2 - 2022 International Conference on Electrical, Control and Information Technology, ECITech 2022
Y2 - 25 March 2022 through 27 March 2022
ER -